AIMC Topic: Spinal Fractures

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Iterative fully convolutional neural networks for automatic vertebra segmentation and identification.

Medical image analysis
Precise segmentation and anatomical identification of the vertebrae provides the basis for automatic analysis of the spine, such as detection of vertebral compression fractures or other abnormalities. Most dedicated spine CT and MR scans as well as s...

Vertebral body insufficiency fractures: detection of vertebrae at risk on standard CT images using texture analysis and machine learning.

European radiology
PURPOSE: To evaluate the diagnostic performance of bone texture analysis (TA) combined with machine learning (ML) algorithms in standard CT scans to identify patients with vertebrae at risk for insufficiency fractures.

Robot-assisted intravertebral augmentation corrects local kyphosis more effectively than a conventional fluoroscopy-guided technique.

Journal of neurosurgery. Spine
OBJECTIVEIntravertebral augmentation (IVA) is a reliable minimally invasive technique for treating Magerl type A vertebral body fractures. However, poor correction of kyphotic angulation, the risk of cement leakage, and significant exposure to radiat...

Deep neural networks for automatic detection of osteoporotic vertebral fractures on CT scans.

Computers in biology and medicine
Osteoporotic vertebral fractures (OVFs) are prevalent in older adults and are associated with substantial personal suffering and socio-economic burden. Early diagnosis and treatment of OVFs are critical to prevent further fractures and morbidity. How...

Combining C-arm CT with a new remote operated positioning and guidance system for guidance of minimally invasive spine interventions.

Journal of neurointerventional surgery
OBJECTIVE: To report our experience using C-arm cone beam CT (C-arm CBCT) combined with the new remote operated positioning and guidance system, iSYS1, for needle guidance during spinal interventions.

Radiomics classification of fresh and old vertebral compression fractures: Impact of compression grade and morphology on diagnostic performance.

European journal of radiology
OBJECTIVES: To develop a radiomics model for identifying fresh or old vertebral compression fractures (VCFs) from CT images, thereby assisting physicians in making more effective decisions.

Deep learning-based identification of vertebral fracture and osteoporosis in lateral spine radiographs and DXA vertebral fracture assessment to predict incident fracture.

Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
Deep learning (DL) identification of vertebral fractures and osteoporosis in lateral spine radiographs and DXA vertebral fracture assessment (VFA) images may improve fracture risk assessment in older adults. In 26 299 lateral spine radiographs from 9...

Vertebral compression fractures at abdominal CT: underdiagnosis, undertreatment, and evaluation of an AI algorithm.

Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
Vertebral compression fractures (VCFs) are common and indicate a high future risk of additional osteoporotic fractures. However, many VCFs are unreported by radiologists, and even if reported, many patients do not receive treatment. The purpose of th...

Deep Learning to Differentiate Benign and Malignant Vertebral Fractures at Multidetector CT.

Radiology
Background Differentiating between benign and malignant vertebral fractures poses diagnostic challenges. Purpose To investigate the reliability of CT-based deep learning models to differentiate between benign and malignant vertebral fractures. Materi...